Plant phenological responses to temperature variation in an alpine meadow

Xiaoting, 李晓婷 Li; Wei, 郭伟 Guo; Xiangnan, 倪向南 Ni; Xiaoyi, 卫晓依 Wei

doi:10.5846/stxb201808221782

Cited by 2 publications

(1 citation statement)

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“…It is a key indication of climate change since it not only represents the current weather but also the accumulation of weather over time. By studying phenology, we may gain a deep understanding of how the local climate changes and how it affects animals and plants (Lieth, 1974;Zhu and Wan, 1975;Zheng, 2002;Xu, 2005;Dai, 2013;Liu, 2018;Zhang, 2018;Li, 2019). Zu and Yang (2016) found that the spring temperature was negatively correlated with the spring phenology of broad-leaved forests, coniferous forests, and meadows while researching the relationship between the phenological changes of various vegetation and climatic factors in Northeast China from 1982 to 2006.…”

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confidence: 99%

Spatiotemporal variations in remote sensing phenology of vegetation and its responses to temperature change of boreal forest in tundra-taiga transitional zone in the Eastern Siberia

Zhuang

et al. 2023

J. Geogr. Sci.

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Phenology is an important indicator of climate change. Studying spatiotemporal variations in remote sensing phenology of vegetation can provide a basis for further analysis of global climate change. Based on time series data of MODIS-NDVI from 2000 to 2017, we extracted and analyzed four remote sensing phenological parameters of vegetation, including the Start of Season (SOS), the End of Season (EOS), the Middle of Season (MOS) and the Length of Season (LOS), in tundra-taiga transitional zone in the East Siberia, using asymmetric Gaussian function and dynamic threshold methods. Meanwhile, we analyzed the responses of the four phenological parameters to the temperature change based on the temperature change data from Climate Research Unit (CRU).The results show that: in regions south of 64°N, with the rise of temperature in April and May, the SOS in the corresponding area was 5-15 days ahead of schedule; in the area between 64°N and 72°N, with the rise of temperature in May and June, the SOS in the corresponding area was 10-25 days ahead of schedule; in the northernmost of the study area on the coast of the Arctic Ocean, with the drop of temperature in May and June, the SOS in the corresponding area was 15-25 days behind schedule; in the northwest of the study area in August and the southwest in September, with the drop of temperature, the EOS in the corresponding areas was 15-30 days ahead of schedule; in regions south of 67°N, with the rise of temperature in September and October, the EOS in the corresponding area was 5-30 days behind schedule; the change of the EOS in autumn was more sensitive to the change of the SOS in spring, because the smaller temperature fluctuation can cause the larger change of the EOS; the growth season of vegetation in the study area was generally moving forward, and the LOS in the northwest was shortened, while the LOS in the middle and south of the study area was prolonged.

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